Patterns of financial crisis: GBP/JPY in 2007-2008.

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Written by Forex Automaton   
Monday, 26 January 2009 15:11

The picture that emerges from the autocorrelation analysis of the GBP/JPY time series on the hour scale looks consistent with what has been previously seen with EUR/JPY, EUR/USD, and GBP/USD. To say that these exchange rates became dramatically more volatile in the second half of 2008 would be to say too little, since one could hypothetically observe very high volatility in a martingale manner, that is without any prehistory dependence whatsoever. The actual pattern of crisis, on the contrary, seems to be characterized by a prehistory dependence of its own, whose essence is the reduced, compared to a hypothetic fully unpredictable time series (no matter how volatile!), likelihood of sustained trends. This is the environment where a trend reversal bet is, everything else being equal, more likely to succeed than a trend continuation bet. To repeat, I am talking about GBP/JPY autocorrelation structure in the hour scale analysis context, not whether the longer-scale movements of the second half of 2008 could be predicted by technical analysis.

Evolution of GBP/JPY exchange rate during the financial crisis, hour.

Fig.1:GBP/JPY during the financial crisis, hour time scale. Time axis is labeled in MM-YY format and spans the interval from August 2, 2007 through December 31, 2008.

I define the visible phase of the present financial crisis to begin on August 16, 2007, the day of Countrywide Financial near-bankruptcy event, followed by an extraordinary half-percent Fed discount rate cut next day. This study covers 74 weeks from August 2, 2007 through December 31, 2008. The sub-range of extreme volatility (as will be seen in Fig.4) can be roughly defined as the last 18 weeks of this 74-week range. In this study, I only look at trading activity taking place from 1am to 1pm New York time, since the experience shows it to be the richest in non-trivial correlations.

GBP/JPY volatility change during the financial crisis, hour.

Fig.2:The histogram of logarithmic returns in GBP/JPY on the hour time scale demonstrates volatility change in the course of the financial crisis.

While the change in the volatility between the beginning of the crisis and its "phase of impact" is indeniable, single-point distributions like Fig.2 do not tell the whole story. These non-Gaussian distributions could belong to a hypothetic random walk or to a more complex behavior where prehistory matters.

Autocorrelation of logarithmic returns in GBP/JPY,  European trading hours, hour scale, from August 2, 2007 through August 27, 2008. Autocorrelation of logarithmic returns in GBP/JPY,  European trading hours, hour scale, from August 28, 2008 through December 31, 2008.

Fig.3: Autocorrelation of logarithmic returns in GBP/JPY for the European (Eurasian) trading shown against the backdrop of statistical noise (red). Top panel: the measurement time range is for the lower volatility phase of the crisis, from August 2, 2007 through August 27, 2008. Bottom panel: same for the high volatility phase, from August 28, 2008 through the end of 2008. The noise is obtained from martingale simulations based on the recorded volatilities of GBP/JPY in the trading hours under study for the period. The noise is presented as mean plus-minus 1 RMS, where RMS characterizes the distribution of the correlation value obtained for each particular bin by analyzing 20 independent simulated uncorrelated time series of the same average volatility. From top to bottom, the shape of the autocorrelation in the vicinity of the zero-time lag peak undergoes a remarkable transformation.

Evolution of GBP/JPY autocorrelation peak structure during the financial crisis, hour.

Fig.4: Evolution of GBP/JPY autocorrelation peak structure during the financial crisis, hour time scale. Time bin is two weeks wide. The peak structure is represented by three correlation values: the one for the zero lag (essentially variance, a volatility measure) downscaled by 10 for easier visual comparison, the one at one hour lag and the one at two hour lag. Time axis is labeled in MM-YY format and spans the interval from August 2, 2007 through December 31, 2008. Only trading hours from 1am to 1pm New York time (European trading hours), usually rich in non-trivial correlations, are included.

Fig.3 shows evolution of the autocorrelation structure from the lower to high volatility phase of the crisis. The evolution is in the same direction as in EUR/JPY, EUR/USD, and GBP/USD: as the volatility goes up, the one hour time lag correlation value drops. Fig.4 traces the evolution of the autocorrelation by focusing on just the three correlation values at specific time lags. The time period of dramatically higher volatility covers the last 9 bins in Fig.4, which contain 18 weeks, from August 28, 2008 through December 31, 2008 (naturally, the choice of dates is to a certain extent forced by the bin width). The near zero time-averaged correlation value at one hour time lag in Fig.3 includes very different contributions. Out of these, the last six weeks of 2008 are marked by consistently bipolar-disorder-like behavior (a.k.a. alternating correlation near zero time lag -- an inclination to form quickly alternating rises and falls on next-hour time scale, more pronounced than in a fully unpredictable time series of the same volatility.) This pattern has been seen before in forex exchange rates with high interest rate differential at stake. It is not new to GBP/JPY and has been reported in the GBP/JPY predictability study covering the time span from August 2002 to January 2008.

Having noticed the difference in the autocorrelation shapes in the vicinity of zero time lag between Fig.3, top panel, and Fig.1 of that original study, I confirm that both are valid -- the difference is due to the trading session time limitation in the present study, absent in the orignial study, and due to the fact that different historical intervals are studied.

This feature is also frequently seen in LIBOR time series analyses. The practical implication of this is simple: since any movement is likely to be followed by the movement in the opposite direction, it is hard to make money on trend following. Rephrasing the Wall Street adage, bulls get slaughtered, bears get slaughtered, pigs get slaughtered, contrarians (and brokers) make money.

The data used are from the period 2002-08-02 00:00:00 to 2009-01-01 00:00:00, New York time.

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Last Updated ( Monday, 04 January 2010 12:41 )